An output feedback attitude tracking controller design for quadrotor unmanned aerial vehicles using quaternion

2013 ◽  
Author(s):  
Chen Diao ◽  
Bin Xian ◽  
Bo Zhao ◽  
Xu Zhang ◽  
Shibo Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Output Feedback ◽  
Controller Design ◽  
Aerial Vehicles ◽  
Attitude Tracking ◽  
Tracking Controller ◽  
Quadrotor Unmanned Aerial Vehicles

scholarly journals Motion Equations and Attitude Control in the Vertical Flight of a VTOL Bi-Rotor UAV

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 208 ◽  
Author(s):  
Sergio Garcia-Nieto ◽  
Jesus Velasco-Carrau ◽  
Federico Paredes-Valles ◽  
Jose Salcedo ◽  
Raul Simarro
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Attitude Control ◽  
Controller Design ◽  
Experimental Studies ◽  
Hardware In The Loop ◽  
Motion Equations ◽  
Design And Implementation ◽  
Aerial Vehicles ◽  
Attitude Tracking ◽  
Tracking Controller

This paper gathers the design and implementation of the control system that allows an unmanned Flying-wing to perform a Vertical Take-Off and Landing (VTOL) maneuver using two tilting rotors (Bi-Rotor). Unmanned Aerial Vehicles (UAVs) operating in this configuration are also categorized as Hybrid UAVs due to their ability of having a dual flight envelope: hovering like a multi-rotor and cruising like a traditional fixed-wing, providing the opportunity of facing complex missions in which these two different dynamics are required. This work exhibits the Bi-Rotor nonlinear dynamics, the attitude tracking controller design and also, the results obtained through Hardware-In-the-Loop (HIL) simulation and experimental studies that ensure the controller’s efficiency in hovering operation.

Adaptive attitude controller design for tail-sitter unmanned aerial vehicles

2020 ◽  
pp. 107754632092535
Author(s):  
Deyuan Liu ◽  
Hao Liu ◽  
Jiansong Zhang ◽  
Frank L Lewis
Keyword(s):  
Adaptive Control ◽  
Unmanned Aerial Vehicles ◽  
Control Method ◽  
Controller Design ◽  
Dynamic Pressure ◽  
Tracking Errors ◽  
Control Approach ◽  
Aerial Vehicles ◽  
Attitude Tracking ◽  
Mode Transitions

Tail-sitter unmanned aerial vehicles have two flight modes: they can fly long distances at high cruising speeds as fixed-wing aircrafts; or hover, take off, and land vertically as rotary-wing aircrafts. The tail-sitter dynamics involves serious nonlinearities and high uncertainties, especially in the two flight mode transitions. In this article, an adaptive control approach is proposed for a class of tail-sitter unmanned aerial vehicles to achieve the robustness properties. The control torque allocation problem is addressed based on the dynamic pressure in the transition flight. The proposed control method does not need to switch the coordinate system, the controller structure, or the controller parameters in different flight modes. It is proven that the attitude tracking errors can converge into a given neighborhood of the origin in finite time. Simulation results are presented to show the advantages of the proposed adaptive control method.

scholarly journals Design of Constructive Controller of Nonlinear System Based on Polynomial Function Growth Condition and Its Application in Deep Subsea Energy Mining and Production Control System

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Longchuan Guo ◽  
Chuanping Zhou ◽  
Xiaoqing Tian ◽  
Huawei Ji ◽  
Yudong Peng
Keyword(s):  
Control System ◽  
Nonlinear System ◽  
Control Problem ◽  
Growth Condition ◽  
Output Feedback ◽  
Controller Design ◽  
Polynomial Function ◽  
Growth Conditions ◽  
Simulation Software ◽  
Tracking Controller

This paper mainly studies the output feedback control problem of the stochastic nonlinear system based on loose growth conditions and applies the research results to the valve control system of underwater oil and gas pipelines, which can improve the speed and stability of the equipment system. First, the concept of randomness is introduced to study the actual tracking control problem of output feedback of stochastic nonlinear systems, remove the original harsher growth conditions, make it meet the more general polynomial function growth conditions, and propose a combination of static and dynamic output feedback practices. The design of the tracking controller makes all the states of the system meet boundedness and ensures that the tracking error of the system converges to a small neighborhood of zero. Second, the system is extended to the parameter-uncertain system, and the output feedback tracking controller with complete dynamic gain is constructed by proving the boundedness of the system state and gain. Further, the time-delay factor is introduced, and the nonlinear term of the system satisfies the more relaxed power growth condition, combined with the inverse method to cleverly construct a set of Lyapunov functions and obtain the output controller to ensure that the system is asymptotically probabilistic in the global scope. Stability. Finally, through the ocean library in the Simulation X simulation software, the controller design results are imported into the underwater electro-hydraulic actuator model to verify the effectiveness of the controller design.

A Two-Step Optimization-Based Iterative Learning Control for Quadrotor Unmanned Aerial Vehicles

2021 ◽  
Vol 143 (7) ◽  
Author(s):  
Revant Adlakha ◽  
Minghui Zheng
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Design Problem ◽  
Iterative Learning Control ◽  
Design Method ◽  
Learning Control ◽  
Iterative Learning ◽  
Learning Performance ◽  
Aerial Vehicles ◽  
Quadrotor Unmanned Aerial Vehicles ◽  
Optimization Based Design

Abstract This paper presents a two-step optimization-based design method for iterative learning control and applies it onto the quadrotor unmanned aerial vehicles (UAVs) trajectory tracking problem. Iterative learning control aims to improve the tracking performance through learning from errors over iterations in repetitively operated systems. The tracking errors from previous iterations are injected into a learning filter and a robust filter to generate the learning signal. The design of the two filters usually involves nontrivial tuning work. This paper presents a new two-optimization design method for the iterative learning control, which is easy to obtain and implement. In particular, the learning filter design problem is transferred into a feedback controller design problem for a purposely constructed system, which is solved based on H-infinity optimal control theory thereafter. The robust filter is then obtained by solving an additional optimization to guarantee the learning convergence. Through the proposed design method, the learning performance is optimized and the system's stability is guaranteed. The proposed two-step optimization-based design method and the regarding iterative learning control algorithm are validated by both numerical and experimental studies.

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